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1.

Application of multistage process control methodology for software quality management Pages 55-66 Right click to download the paper Download PDF

Authors: Boby John, R. S. Kadadevaramath, I. A. Edinbarough

DOI: 10.5267/j.jpm.2017.2.001

Keywords: Quantitative project manage-ment, Defect density, Classification and regression tree, Ridge regression, Multistage process control

Abstract:
As the need for software increased, the number of software firms and the competition among them also increased. The software companies in developing countries like India can no longer survive based on cost advantage alone. The firms need to deliver competitively priced quality software products on time. This can be achieved through quantitatively managing the different phases or sub processes in software development process. But quantitative management of a process consisting of a set of interlinked sub processes or stages with the output of one sub pro-cess influencing that of subsequent stages and final output is not easy. The process performance models developed for quantitative management of software development process often model the final outcome in terms of factors from various stages together or focuses only on quantitatively managing a particular sub process independently. In manufacturing and other engineering indus-tries, the processes with multiple sub process are monitored and controlled using multistage pro-cess control methodology. This paper is an application of multistage statistical process control for managing the software development process. The suggested methodology is a combination of process performance models and control charts. The proposed methodology can be easily im-plemented for controlling various types of software projects like development projects, incre-mental development projects, testing projects etc. The methodology also provides the project manager the opportunity to tighten or relax the control at various sub processes based on the pro-ject team’s strengths and still achieve the goal on the final outcome.
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Journal: JPM | Year: 2016 | Volume: 1 | Issue: 2 | Views: 1903 | Reviews: 0

 

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